{"id":"W2967741816","doi":"","title":"Social Media Data, Machine Learning and Causal Inference","year":2019,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Social media; Artificial intelligence; Causal inference; Inference; Machine learning; Data science; Natural language processing; World Wide Web; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04145156,0.001595226,0.001405722,0.007945511,0.002624331,0.006451243,0.00292137,0.002877975,0.004996682],"category_scores_gemma":[0.1298683,0.001116965,0.00156114,0.007208907,0.01108728,0.0120118,0.004888733,0.00497237,0.0004506946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003546745,"about_ca_system_score_gemma":0.004378387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00463547,"about_ca_topic_score_gemma":0.004261572,"domain_scores_codex":[0.961206,0.03128122,0.001165953,0.002951125,0.002989647,0.0004061037],"domain_scores_gemma":[0.6851702,0.2832602,0.01280252,0.01413163,0.003654404,0.0009811328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007600052,0.0002117003,0.009477059,0.0009234377,0.000428663,0.0003269181,0.001671564,0.02098235,0.0003024777,0.9108339,0.00333654,0.05142939],"study_design_scores_gemma":[0.00002707202,0.00002697324,0.001233986,0.0002222152,0.00004096327,0.00007247744,0.0004675467,0.04031701,0.0003383133,0.9519707,0.005250269,0.0000323272],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02401426,0.003205932,0.946983,0.01394006,0.000382829,0.0005188452,0.00142752,0.0002876001,0.009239951],"genre_scores_gemma":[0.4801743,0.003497748,0.508431,0.001909874,0.001098529,0.002003866,0.001260569,0.0001136221,0.001510604],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04145156,"threshold_uncertainty_score":0.2192194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04886245868015036,"score_gpt":0.368742220054924,"score_spread":0.3198797613747736,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}